Medium Risk

update_table

Re-run validation on a previously processed table (update in place). source_version can pin a specific prior result version; omit for latest.

Part of the Hyperplexity server.

update_table can modify Hyperplexity data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents use update_table to create or modify resources in Hyperplexity. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

Without a policy, an AI agent could call update_table repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Hyperplexity.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "update_table": {
      "limits": [
        {
          "counter": "update_table_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Hyperplexity policy for all 16 tools.

Get this rule live on your own Hyperplexity server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access update_table gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so update_table only ever does what you allow.

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Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the update_table tool do? +

Re-run validation on a previously processed table (update in place). source_version can pin a specific prior result version; omit for latest.. It is categorised as a Write tool in the Hyperplexity MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on update_table? +

Register the Hyperplexity MCP server in PolicyLayer and add a rule for update_table: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Hyperplexity. Nothing to install.

What risk level is update_table? +

update_table is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit update_table? +

Yes. Add a rate_limit block to the update_table rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block update_table completely? +

Set action: deny in the PolicyLayer policy for update_table. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides update_table? +

update_table is provided by the Hyperplexity MCP server (hyperplexity/hyperplexity). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Hyperplexity tool call.

Deterministic rules across all 16 Hyperplexity tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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